ITSC 2025 Paper Abstract

Paper VP-VP.37

Cui, Chenyang (Tsinghua University), Li, Xingyu (Tsinghua University), HU, Jianming (Tsinghua University)

TrainBEV: Railway Foreign Invasion Detection System Based on BEV Representation

Scheduled for presentation during the Video Session "On-Demand Video Presentations" (VP-VP), Saturday, November 22, 2025, 08:00−18:00, On-Demand Platform

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on April 2, 2026

Keywords Advanced Sensor Fusion for Robust Autonomous Vehicle Perception, Real-time Object Detection and Tracking for Dynamic Traffic Environments, Sensor Integration and Calibration for Accurate Localization in Dynamic Road Conditions

Abstract

对轨道交通日益增长的需求提高了铁路安全的重要性，轨道侵入异物是导致铁路的主要原因之一事故。然而，电流轨旁传感基础设施仍然不发达，使得远程障碍物检测是一项关键且具有挑战性的任务。我们提出铁路的全面认知框架基于 Bird's Eye View 的外来入侵检测（BEV）表示，受到自动驾驶。我们的系统集成了多个组件，包括在线多传感器校准模块、轨道分割模块和 3D 外部入侵检测模块。通过将两者合并多传感器和时间融合策略，该框架有效增强感知稳健性准确性。在 OsDAR23 铁路上进行广泛实验数据集证明，我们的ਬ